Second Generation Mothers - Do the children of immigrants adjust their fertility to host country norms?
Bibliographic record
Abstract
For many countries, like the United States, Canada and Australia, immigration has played an important role in the settlement processes. In Sweden, immigration has been a largely post-war phenomenon, but it has nevertheless served as an important input for the transformation of Swedish society and has left an imprint on the composition of the Swedish population that could not be foreseen 50 years ago. From numbering fewer than 100,000 in 1945, the foreign-born population in Sweden had increased to 1.2 million in 2008, and Statistics Sweden projects that this number will reach 1.7 million in the year 2050. Initially, migrants to Sweden were fleeing the horrors and destruction of World War II in Europe, but shortly after the war labor force migration from the neighboring Nordic countries and Southern Europe became the dominant force. In the early 1970s the face of immigration changed and has since been dominated by refugee and family reunification migration from a wide range of countries from all over the world. The widespread demand for manual and industrial labor which was an important determinant of immigration streams in the 1950s and 1960s became less important and, since the early 1970s, migration policy and the outbursts of war, famine and terror on behalf of anti-democratic regimes have largely determined the streams of immigrants to Sweden. This intense and multi-faceted immigration experience resulted in the varied society of today. Not only does Swedish society contain a large immigrant population, but the children of immigrants, also known as the second generation, make up a sizeable and growing fraction of the Swedish population. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".